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20 results for “PhD students”

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cs.SEEmpiricalRecentJul 27, 2026

Motivations and Barriers to Communicating Software Engineering Research: Insights from Early Career Researchers

Shalini Chakraborty, Marvin Wyrich, Sven Apel, Sebastian Baltes

This paper investigates how PhD students in software engineering perceive and navigate science communication, revealing motivations, communication channels, and barriers.

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cs.DCEmpiricalRecentJun 30, 2026

An Empirical Analysis of High-Performance Computing Education in Germany

Anna-Lena Roth, Jonas Posner

This paper assesses HPC education at 102 academic institutions in Germany, identifying 178 HPC-related courses and evaluating their competency coverage and curricular placement, as well as examining l…

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cs.NEEmpiricalRecentJul 25, 2026

A genetic algorithm for student academic resource allocation

Ana F. Hernández, Andrej Franulic, Fernando Jiménez

This paper proposes a Genetic Algorithm with constraint repair mechanism for optimally allocating educational resources to high school mathematics students under study time constraints.

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cs.CRcs.CYRecentMay 19, 2026

Locked Out at 8,000 Miles: Why UK-China Partnership Students Are Suffering

Benjamin Kenwright

The paper argues that over-engineered university cybersecurity protocols, while necessary, create significant accessibility barriers that disproportionately harm remote international students, particu…

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cs.HCEmpiricalRecentJun 12, 2026

Visible Adoption, Untracked Contribution: GitHub Evidence of the Accountability Gap Across Three Cohorts of an HCI Prototyping Course

Maria Teresa Parreira, Pranav Prabhat Sinha, Hauke Sandhaus, Wendy Ju

This paper analyzes the shift in student adoption and accountability practices of GenAI tools in a graduate-level HCI prototyping course across three cohorts using GitHub data.

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cs.DLcs.CYcs.IREmpiricalRecentJun 23, 2026

Is Higher Team Gender Diversity Correlated with Better Scientific Impact?

Chengzhi Zhang, Jiaqi Zeng, Yi Zhao

This paper investigates the correlation between gender diversity and the scientific impact of papers in Natural Language Processing (NLP) and Library and Information Science (LIS) domains.

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cs.AIRecentMay 27, 2026

Practitioner Beliefs and Behaviors in AI-Enhanced Education: DOT Framework Survey Evidence

David Gibson, M. Elizabeth Azukas, Gerald Knezek

This study surveyed higher education practitioners to map their beliefs and behaviors regarding AI integration, finding that while they view AI favorably, institutional barriers and gaps in design-ori…

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cs.IRcs.AIcs.CYRecentMay 27, 2026

Whose Name Comes Up? III: Persona Prompting Effects in LLM-Based Scholar Recommendation

Annabella Sánchez-Guzmán, Lukas Eberhard, Denis Helic, Lisette Espín-Noboa

The paper proposes a comprehensive benchmark to systematically audit how varying persona prompts and model choices affect the technical quality and social representativeness of scholar recommendations…

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cs.ROcs.AIEmpiricalRecentJul 24, 2026

Teachy Mini: Development and Preliminary Evaluation of a Knowledge-Based Generative Social Robot for Higher Education

Stephan Vonschallen, Karim Kaufmann, Dominique Oberle, Friederike Eyssel +1 more

This paper operationalizes knowledge-based design requirements in a generative social robot tutoring system called Teachy Mini, and evaluates its effectiveness in higher education.

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cs.DCEmpiricalRecentJun 30, 2026

Performance Analysis in Parallel Programming Education: A Comparative Usability Study

Anna-Lena Roth, David James, Jonas Posner, Michael Kuhn

The paper introduces EduMPI, a learning support tool for simplifying cluster usage and performance analysis of MPI parallel programs for students.

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cs.HCcs.AIEmpiricalRecentJun 27, 2026

Exploring the Value of Diverse LLM Explanations in Introductory Programming

Seth Bernstein, Paul Denny, Juho Leinonen, Kush Patel +3 more

This paper explores the effectiveness of diverse LLM-generated explanations versus generic explanations in computer science education, finding that diverse explanations led to higher open-ended respon…

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econ.GNcs.CLcs.MAEmpiricalRecentJul 16, 2026

Does Multi-Agent Debate Improve AI Feedback on Research Papers?

Tomas Havranek, Zuzana Irsova

Authors of 44 meta-analyses preferred a single pass by a frontier model over two multi-agent debate tools for improving their papers, despite the tools spending roughly thirty times the tokens.

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cs.AIcs.HCEmpiricalRecentJul 9, 2026

Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis

Kristina Schaaff, Quintus Stierstorfer, Valerie Heckel

This paper presents a large-scale analysis of AI-based learning assistant (Syntea) usage in higher education using log data from 77,543 students.

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cs.CYcs.HCEmpiricalRecentJul 17, 2026

Student Evaluation of Repeated AI Feedback Across a Semester of Writing

Andres Karjus, Janika Leoste, Tiia Õun

This paper analyzes the use of generative AI for feedback in higher education based on 2988 instances from Estonian bachelor students, finding that students generally find it helpful but not a self-co…

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cs.HCcs.AIcs.CYNEWEmpiricalJul 29, 2026

Human diversity fuels collective creativity that large language models cannot simulate or sustain

Mengchen Dong, Hiromu Yakura

This paper investigates how AI affects human creativity and diversity in a language experiment with English writers.

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cs.AIcs.CYcs.MAEmpiricalRecentJun 29, 2026

Clarus: Coordinating Autonomous Research Agents toward Web-Scale Scientific Collaboration

Zihan Guo, Zeyi Chen, Zhiyu Chen, Zicai Cui +14 more

This paper presents Clarus, a collaboration infrastructure for coordinating autonomous research agents towards web-scale scientific collaboration.

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cs.SEEmpiricalRecentJul 17, 2026

What Does It Take to Research with AI? A Rapid Review of Competencies to Train LLM-Literate Researchers

Danilo Monteiro Ribeiro, Ronnie de Souza Santos, Rodrigo Siqueira, Breno Andrade +4 more

This paper identifies eight competencies required for researchers and graduate students to use Large Language Models critically and responsibly, based on a review of 40 articles.

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cs.NEcs.AIcs.CESurveyRecentJul 10, 2026

Evolutionary Intelligence for Scientific Discovery: From Evolutionary Computation to Cumulative Discovery Systems

Chao Wang, Lingling Li, Fang Liu, Licheng Jiao

This paper proposes Evolutionary Intelligence (EI) for scientific discovery, which links candidate refinement with experience retention across evolutionary cycles.

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cs.DCcs.AIcs.LGEmpiricalRecentJun 26, 2026

Optimizing Teacher-Student Partitioning for Scalable Knowledge Distillation on HPC Systems

Adrian P. Dieguez, Victor Conchello Vendrell, Alex Batlle, Vinnam Kim +2 more

This paper proposes an HPC-aware methodology for Knowledge Distillation (KD) that decouples teacher and student partitioning efficiently, achieving up to 67% higher samples-per-second than the widely…

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